Optimization of boron removal from water by electrodialysis using response surface methodology.

Boron removal from water containing 5 mg L-1 of boron using electrodialysis (ED) was studied as a function of several parameters such as flow rates, initial pH, coexisting anions and ED time. An ED cell, equipped with three cation exchange membranes (fumasep FKB) and two anion exchange membranes (fumasep FAB), was applied. The central composite design, which is the standard design of response surface methodology, was used to evaluate the effects and interactions of studied factors on boron removal efficiency. The effectiveness of the considered design parameters was well examined to find the optimum condition. The experimental data obtained were analyzed by analysis of variance for the polynomial model with 95% confidence level. Boron removal by ED showed to be independent of the electrodialysis time, whereas flow rate as well as the pH of the feed solution and also the coexisting anions on the feed solution play a significant role on the deboronation efficiency. According to the desirability function, the maximum response of 43.5% was predicted for boron removal at a pH equal to 10, a flow rate of 10 L h-1, a ratio between sulfates and that of boron equal to 2 and a reaction time of 25 minutes.

Application of response surface methodology and artificial neural network: modeling and optimization of Cr(VI) adsorption process using Dowex 1X8 anion exchange resin.

We report the adsorption efficiency of Cr(VI) on a strong anionic resin Dowex 1X8. The Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analysis of this adsorbent were investigated. Response surface methodology was applied to evaluate the main effects and interactions among initial pH, initial Cr(VI) concentration, adsorbent dose and temperature. Analysis of variance depicted that resin dose and initial pH were the most significant factors. Desirability function (DF) showed that the maximum Cr(VI) removal of 95.96% was obtained at initial pH 5, initial Cr(VI) concentration of 100 mg/L, resin dose of 2 g and temperature of 283 K. Additionally, a simulated industrial wastewater containing 14.95 mg/L of Cr(VI) was treated successfully by Dowex 1X8 at optimum conditions. Same experimental design was employed to develop the artificial neural network. Both models gave a high correlation coefficient (RRSM(2) = 0.932, RANN(2) = 0.996).

Sustainable removal of caffeine and acetaminophen from water using biomass waste-derived activated carbon: Synthesis, characterization, and modelling.

The removal of caffeine (CFN) and acetaminophen (ACT) from water using low-cost activated carbons prepared from artichoke leaves (AAC) and pomegranate peels (PAC) was reported in this paper. These activated carbons were characterized using various analytical techniques. The results showed that AAC and PAC had surface areas of 1203 and 1095 m2 g-1, respectively. The prepared adsorbents were tested for the adsorption of these pharmaceuticals in single and binary solutions. These experiments were performed under different operating conditions to evaluate the adsorption properties of these adsorbents to remove CFN and ACT. AAC and PAC showed maximum adsorption capacities of 290.86 and 258.98 mg g-1 for CFN removal, 281.18 and 154.99 mg g-1 for the ACT removal over a wide pH range. The experimental equilibrium adsorption data fitted to the Langmuir model and the kinetic data were correlated with the pseudo-second order model. AAC showed the best adsorption capacities for the removal of these pharmaceuticals in single systems and, consequently, it was tested for the simultaneous removal of these pollutants in binary solutions. The simultaneous adsorption of these compounds on AAC was improved using the central composite design and response surface methodology. The results indicated an antagonistic effect of CFN on the ACT adsorption. AAC regeneration was also analyzed and discussed. A statistical physics model was applied to describe the adsorption orientation of the tested pollutants on both activated carbon samples. It was concluded that AAC is a promising adsorbent for the removal of emerging pollutants due to its low cost and reusability properties.

Intensification of light green SF yellowish (LGSFY) photodegradion in water by iodate ions: Iodine radicals implication in the degradation process and impacts of water matrix components.

The results of this work showed that UV/IO3- oxidation process supplies good performance in the degradation of light green SF yellowish (LGSFY) dye in deionized water. This process generated reactive iodine radicals that make the degradation much faster than the sole UV irradiation. The assistance of UV-irradiation by 10 mM of iodate increased the LGSFY removal after 10 min from 36% to 90% for C0 = 10 mg/L and from 18% to 85% for C0 = 20 mg/L. In parallel, a 2.5 and 4.72-fold increase in the LGSFY initial degradation rate, as compared with UV alone, were recorded for, respectively, 10 and 20 mg/L of LGSFY. IO2 and IO played the most important role in the degradation of LGSFY by the UV/IO3- process. The degradation was not affected by the presence of chloride and nitrate ions even at high dosage levels (up to 0.1 M), whereas sulfate ions reduced the valuable effect of iodate to the half when they are present at 0.1 M. Correspondingly, humic acids, at usual concentrations as those measured in natural waters, did not affect significantly the LGSFY degradation upon photoactivated iodate process. These results revealed, in one part, that iodine radicals are selective oxidants and, in another part, that the process is likely to remove organic dyes from natural water which often contains mineral constitutes and humic substances.